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WHEN THE SMART GRID MEETS ENERGY-EFFICIENTCOMMUNICATIONS: GREEN WIRELESS CELLULAR
NETWORKS POWERED BY THE SMART GRID
Authors
S. Bu, F. R. Yu, Y. Cai, and X. P. Liu
IEEE Transactions on Wireless Communications, Aug. 2012
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Outline
1. Introduction
2. System Model
3. Problem Formulation
4. Analysis of the Proposed Two level Game
5. Simulation Results and Discussions
2
1. Introduction
6. Conclusion
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1. Introduction
Green Communications Network Design
Objectives:
1. Reduce the amount of energy consumption by
the networks’ BSs
2. Maintain a satisfactory QoS for the users
3
Motivations for Green Radio Communications
Service Provider’s
Financial Considerations
Environmental
Considerations
- Half of annual operating
expenses are energy costs
- Currently, 2% of CO2
emissions from telecom.
E n er g y C on s u
m pt i on
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1. Introduction Cont.
Solutions for Energy Aware Infrastructure
Renewable
Energy Sources
Heterogeneous
Cell Sizes
Dynamic
Planning
- Reduce CO2emissions by using
renewable energy
- Reliability issues
- Macro-cells Femto-cells
- Balance of
different cell sizes
is required
- Exploit trafficload fluctuations
- Switch off
available resources
at light traffic load
4
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1. Introduction Cont.
Temporal fluctuations in traffic load
Resources on-off Switching
Radio transceivers of
active BSs
Entire BS switch-off
5
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1. Introduction Cont.
Dynamic planning challenges
Service Provision Guarantee
Increase cell
radii
Relaying
mechanism
Network
cooperation
- Coverageholes & inter-cell
Interference
- Unreliable fordelay sensitive
applications
- Alternatelyswitch on-off
resources
6
CoMP
Extend BSs coverage area
Ensure service quality for users in off cells
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1. Introduction Cont.7
Wireless Cellular Network Powered by the Smart Grid
Consider not only energy efficient communications but also the
dynamics of the smart grid in designing green wireless cellularnetworks
Dynamic operation of BSs
depends on: traffic, real time
electricity price provided by SG,
and pollutant level associated
with electricity generation
Active BSs decide on which retailers to
procure electricity from and how much
electricity to procure, considering the
pollutant level of each retailer and the
price offered by the retailer
Novelty
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Outline
1. Introduction
2. System Model
3. Problem Formulation
4. Analysis of the Proposed Two level Game
5. Simulation Results and Discussions
8
6. Conclusion
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2. System Model9
• Cellular network powered by the smart grid
Real-time pricing DSM in SG CoMP & service blocking BSs electricity consumption
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2. System Model Cont.10
A. Real time pricing DSM:
• Dynamic pricing: effective DSM strategy to encourage users
to consume electricity more wisely• Electricity market liberalization: retailers compete with each
other and aim to achieve the highest individual profits by
adjusting the price offered to users in each region
• Real time pricing: prices offered by retailers changefrequently to reflect variations in the cost of the energy
supply
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2. System Model Cont.11
B. CoMP Communication:
• BSs are turned off when
traffic is low, real timeprice is too high, or
pollutant level of the
electricity retailer is too
high
• CoMP is used among active BSs to guarantee the coverage
requirements
• Assume i BSs in each CoMP cooperation cluster
• All possible combinations of BSs in the cluster are 2 ,
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2. System Model Cont.12
C. Service Blocking:
• The uplink sum capacity for the cluster is given by
Identity
matrixTerminal
power
Channel
matrix
• The number of channel available in cluster is given by
BW allocated
for each CoMP
cluster
Effective BW required for
service, considers packet-
level QoS (delay, loss)
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2. System Model Cont.13
• Service blocking probability in each cluster is given by
Traffic arrival rate
Average service
rate
•Relationship between service blocking probability and acombination set is given by
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2. System Model Cont.14
D. BSs Electricity Consumption Model:
• Active BS energy consumption is given by
BS Transmission Power
Account for antenna
setting, carrier freq.Path loss
exponent
Inter-site
distance
Signal Processing Power
Base line signal
processing per BS
Backhaul Power
Req.
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2. System Model Cont.15
• Active BS energy consumption is summarized as
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Outline
1. Introduction
2. System Model
3. Problem Formulation
4. Analysis of the Proposed Two level Game
5. Simulation Results and Discussions
16
6. Conclusion
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3. Problem Formulation17
Two steps:
1. Each retailer in the smart grid provides the real-time price
to the BSs in each cluster
2. Each cluster decides how many BSs turned on, and how much
electricity to procure from each retailer
Stackelberg Game
Leaders Followers
Each retailer in the SG BSs in one clusterSG level Game Cellular network
level Game
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3. Problem Formulation Cont.18
A. Cellular Network Level Game:
• BSs Obj.: obtain the lowest service blocking probability with
least possible costs
• BSs decide, to maximize a net utility:
1. How many BSs will be active in a cluster?
2. How much electricity is procured from each retailer?
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3. Problem Formulation Cont.19
• Net utility of all BSs in a cluster:
Service blocking utility function Total electricity cost Total pollutant level
• BSs Optimization Problem:
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3. Problem Formulation Cont.20
B. Smart Grid Level Game:
• Retailer n utility function is given as:
• Retailer n Optimization Problem:
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Outline
1. Introduction
2. System Model
3. Problem Formulation
4. Analysis of the Proposed Two level Game
5. Simulation Results and Discussions
21
6. Conclusion
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4. Analysis of the Proposed Game22
• Refer to paper for proof of: 1. Existence; and 2. Uniqueness
of the Stackelberg equilibrium
A. Analysis of Cellular Network Level Game:
• Find Lagrangian of the cellular network optimization problem
• Find derivative of the Lagrangian w.r.t. the electricity quantity
and equate it to zero
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4. Analysis of the Proposed Game Cont.23
B. Analysis of Smart Grid Level Game:
Solve for
Iteration Step size
=
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Outline
1. Introduction
2. System Model
3. Problem Formulation
4. Analysis of the Proposed Two level Game
5. Simulation Results and Discussions
24
6. Conclusion
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5. Simulation Results & Discussions25
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5. Simulation Results & Discussions Cont.26
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5. Simulation Results & Discussions Cont.27
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5. Simulation Results & Discussions Cont.28
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Outline
1. Introduction
2. System Model
3. Problem Formulation
4. Analysis of the Proposed Two level Game
5. Simulation Results and Discussions
29
6. Conclusion
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6. Conclusion30
• How the cellular network dynamic operation based on traffic
arrival rate, electricity real-time price, and pollutant levels of
retailers can reduce the operational expenditure and pollution
level
• CoMP is used to extend BSs coverage area and reduce
blocking probability for the off-cells
• Stackelberg game formulation